Day One | Day Two | Day Three | Short Courses
Wednesday, September 28
8:00 am Breakfast Presentations (Sponsorship Opportunities Available) or Morning Coffee
8:45 Chairperson’s RemarksTom Richissin, Regional Territory Manager, Isilon division of EMC
8:50 The Future of Pathology and Personalized Medicine in the Cloud
Dennis P. Wall, Ph.D., Assistant Professor, Pathology, Beth Israel Deaconess Medical Center & Center for Biomedical Informatics, Harvard Medical School
For personalized medicine to become a mainstay in primary care, it must be coupled closely with clinicians working directly in the hospital enterprise rather than diffused across independent research groups. To ensure this coupling, we have begun to transform individualized whole-genomic data into actionable decision support from directly within the diagnostic cornerstone of the hospital, Pathology. In this talk, we will describe our efforts to process and integrate personal genomes into the electronic medical record with particular focus on how we use cloud infrastructure to keep pace with the increasingly large computational demands associated with personalized medicine. Finally ,we will explain how our effort in total — from the sequence to the cloud to the clinic — will enable widespread adoption and penetration of whole-genomic medicine into clinical practice such that the promise of personalized medicine is achieved.
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9:20 Driving Forward Looking in the Rear-View Mirror: Big Data Management in NGS
Sanjaya Joshi, Solutions Architect, Life Sciences, Isilon division of EMCThe number of NGS runs and the data they produce are growing exponentially. Mr. Joshi will present a reference architecture within a data management perspective for NGS and associated data metrics as a Management Information Base (MIB) concept for Big Data. He will also provide a brief introduction to future architectures and approaches for NGS data.
9:50 Selected Poster Presentation: Mapping of the Mammalian Photoreceptor Transcription Network by ChIP-SeqHong Hoa, Ph.D., Research Fellow, Neurobiology Neurodegeneration and Repair Laboratory, National Eye Institute, NIH
10:05 Networking Coffee Break in the Exhibit Hall with Poster Viewing
10:45 MPromDb: A Next-Gen Sequencing
Data Management Platform for Transcriptional and Epigenomic Studies
Ramana Davuluri, Associate Professor, Computational Biology, Wistar Institute
We have designed an integrated bioinformatics platform for identifying and annotating mammalian gene (both coding and non-coding) promoters, associated epigenetic modifications and transcription factor binding profiles from ChIP-Seq datasets and the expression of the corresponding transcripts from RNA-seq datasets. The integrated transcriptome data is stored and regularly updated in a user-friendly database, known as Mammalian Promoter Database (MPromDb). Users can search the database for gene promoters using multiple search criteria. I will discuss the database, associated bioinformatics pipelines and its utility as an integrated resource for mammalian gene transcriptional regulation and epigenomic studies.
11:15 Annotating Non-Coding Regions of the Genome
Mark Gerstein, Ph.D., Professor, Biomedical Informatics, Molecular Biophysics, Biochemistry, Computer Science, Yale University
A central problem for 21st century science is annotating the human genome and making this annotation useful for the interpretation of personal genomes. My talk will focus on annotating the bulk of the genome that does not code for canonical genes, concentrating on intergenic features such as TF binding sites, non-coding RNAs (ncRNAs), and pseudogenes (protein fossils). I will describe an overall framework for data integration that brings together different evidence to annotate features such as binding sites and ncRNAs. Much of this work has been carried out within the ENCODE and modENCODE projects, and I will describe my approach interchangeably both in human and various model organisms (e.g. worm). I will further explain how many different annotations can be inter-related to characterize the intergenic space, build regulatory networks, and construct predictive models of gene expression from chromatin features and the activity at binding sites.
11:45 Close of Morning Session
12:00 pm Luncheon Presentations (Sponsorship Opportunities Available) or Lunch on Your Own
1:30 Chairperson’s Remarks
Stuart M. Brown, Ph.D., Associate Professor, Cell Biology; Director, Research Computing Resource, New York University Langone Medical Center
1:35 Using DNaseI Sequencing Data to Infer the Locations of Bound Transcription Factors and to Understand the Connection between Transcription Factor Binding, Chromatin Openness and Gene Expression
Jacob Degner, Ph.D. Candidate, Human Genetics, Committee on Genetics Genomics and Systems Biology, University of Chicago
Presented will be both recently published results on using DNaseI cutsite data to infer binding for hundreds of transcription factors simultaneously as well as our recent work in which we have collected DNaseI sequencing data across 70 HapMap individuals. We find that the correspondence between our inference of binding is highly correlated will data from independent ChIP-seq experiments from the ENCODE project. Furthermore, in our application across individuals, we find evidence for ~3000 cis-associated genetic variants affecting chromatin openness and find that many of these variants fall within our inferred transcription factor binding sites.
2:05 SAMMate: A GUI Pipeline for RNA-Seq Data Analysis from de novo Assembly to Isoform Quantification
Dongxiao Zhu, Ph.D., Assistant Professor, Computer Science, Wayne State University
In SAMMate 2.5, users are able to take SAM/BAM files as the input and quantify transcriptome at the isoform level. Three algorithms were available for this purpose. Other features include exporting wiggle files for visualization on a genome browser and signal maps for change detection. Soon we will incorporate alignment modules using Bowtie, which will allow users to provide raw read data in fastq/fasta format as input to SAMMate. Before September, we will design and implement another de novo assembly module for users to quantify novel transcripts.
2:35 Digging Deeper into RNA-Seq Data
Stuart M. Brown, Ph.D., Associate Professor, Cell Biology; Director, Research Computing Resource, New York University Langone Medical Center
Many validated methods exist to measure gene expression using RNAseq data. However, it is much more difficult to obtain robust measurements of changes in alternative splicing across samples and avoid false discovery. We have benchmarked some open source tools that quantify alternative transcripts and we have developed new tools to measure exon-specific expression as
well as a simple QC tool to estimate 3’ bias in each sample of RNAseq data.
3:05 Networking Refreshment Break in the Exhibit Hall with Poster Viewing
3:25 Chairperson's Remarks
Kevin Davies, Ph.D., Editor-in-Chief, Bio-IT World
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3:30 Poster Award Winners Announced
3:35 High-Throughput Single Molecule Mechanical Sequencing of DNA
Vincent Croquette, Ph.D., Director of Research, Physical Statistics, École Normale Supérieure, Paris
Single molecule DNA sequencing can be done by detecting the positions of roadblocks (e.g. hybridized fragments) during rehybridization of a mechanically unzipped DNA. It can be implemented via sequencing by hybridization, ligation or polymerization. That technique is high-throughput and does not require the use of labeled nucleotides.
4:05 Sample in, Answer out: Clinical Sequencing Workflows on the GnuBIO Platform
John Healy, Vice President, Informatics, GnuBIO, Inc.
GnuBIO’s sequencing technology is the first to enable clinical workflows on a single platform. An entire targeted sequencing run, from enrichment to sequencing to analysis, can be performed from a single touch point. The high-throughput, serial nature of the underlying emulsion-based microfluidics results in cost and turnaround times that scale linearly as a function of the number of samples and targets sequenced, rather than per run. The GnuBIO platform produces read lengths measured in the hundreds of bases, combined with per-base accuracies well above 99.9% bringing rare variants, linkage studies and structural events within reach. This unique set of capabilities is the first to satisfy the requirements of sequencing applications aimed to directly impact the clinical decision process.
4:35 Towards Optipore Single-Molecule DNA Sequencing
Amit Meller, Ph.D., Associate Professor, Biomedical Engineering and Physics, Boston University
We describe a novel method for high-throughput DNA sequencing based on threading of individual DNA molecules in nanopore arrays and optical readout. The method takes advantage of the extremely high sensitivity of solid-state nanopores, and the parallel nature of the optical detection, which permits probing from hundreds of nanopores fabricated at high density. The combination of single-molecule sensitivity, high-speed and parallel detection will allow us to achieve an extremely high sequencing throughput, making our technology attractive for in vitro diagnostic applications.
5:05 Close of Meeting